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Wafer Defect Detection

Detection output on a sample optical lens image: defective regions are segmented and highlighted, with defect classification overlaid

A C++ and OpenCV based computer vision system for automated detection and classification of defects on semiconductor wafer surfaces. Designed to segment defective regions from high-resolution wafer imagery and identify defect type.

Built as a proof-of-concept for inline inspection in semiconductor manufacturing workflows

Setup:

  1. Clone the repository to your local machine.
git clone https://github.com/vetrivln/WaferDefectDetection
  1. Add OpenCV to your project:
  • Include directories -> opencv\build\include
  • Library directories -> opencv\build\x64\vc16\lib
  • Link .lib files -> opencv_world4xx.lib
  1. Build and Run the project in Visual Studio.

Requirements:

  • OS: Windows 10/11 (64 bit)
  • Compiler: Visual Studio 2019/2022
  • OpenCV: 4.x
  • .NET: 4.7.2 or higher